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Learning path

Vector Stores

Skill Level
Intermediate
Duration 2 hours 50 minutes
Updated Jun 4, 2026

About this learning path

This learning path covers vector search from concept to practice. Articles explain vectors, embeddings, similarity metrics, and vector store software — including how to choose the right database and index type. The hands-on lab then stress-tests embedding models, compares distance metrics, evaluates models of different sizes, and builds a framework for tuning chunking and measuring retrieval quality.

Your instructors

Sam BurckWorld Wide TechnologySr Data Scientist

Prerequisites

  1. Python
  2. A basic understanding of retrieval in RAG and AI Systems.

What you'll learn

  1. How text is represented numerically in vector-based retrieval strategies
  2. How text embeddings fail to capture certain elements around what the text actually means
  3. How to test and tune your retrieval systems so they perform at their best
  4. An overview of the most popular software solutions for vector storage and retrieval
ATC+
Learning path
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Vector Stores
  1. 1. Vector Stores
    1. Enroll in this learning path to view locked contentVector Fundamentals: From Words to Numbers
      Article
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    2. Enroll in this learning path to view locked contentEmbeddings: How they work and what to watch out for
      Article
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    3. Enroll in this learning path to view locked contentSimilarity Search and Measurement
      Article
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    4. Enroll in this learning path to view locked contentVector Store Indexes and Their Tradeoffs
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    5. Enroll in this learning path to view locked contentVector Stores: The Software Landscape
      Article
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    6. Enroll in this learning path to view locked contentVector DBs and Semantic Search
      Lab
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  2. 2. Conclusion
    1. Enroll in this learning path to view locked contentVector Store Quiz
      Quiz
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    2. Enroll in this learning path to view locked contentLearning Path Complete
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